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EDITORIAL published: 05 April 2017 doi: 10.3389/fnhum.2017.00165

Editorial: Trends in Neuroergonomics

Klaus Gramann 1, 2*, Stephen H. Fairclough 3, Thorsten O. Zander 1, 4 and Hasan Ayaz 5, 6, 7

1 Department of and Ergonomics, Berlin Institute of Technology (TU Berlin), Berlin, Germany, 2 Center for Advanced Neurological Engineering, University of California, San Diego, San Diego, CA, USA, 3 School of Natural Sciences and Psychology, Liverpool John Moores University, Liverpool, UK, 4 Team PhyPA, Berlin Institute of Technology (TU Berlin), Berlin, Germany, 5 School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA, 6 Department of Family and Community Health, University of Pennsylvania, Philadelphia, PA, USA, 7 Division of General Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

Keywords: neuroergonomics, human-machine interaction, brain-computer interface, mobile brain/body imaging, physiological computing, EEG/ERP, NIRS/fNIRS, tDCS

Editorial on the Research Topic

Trends in Neuroergonomics

NEW METHODS IN NEUROERGONOMICS

This Research Topic is dedicated to Professor Raja Parasuraman who unexpectedly passed on March 22nd 2015. Raja Parasuraman’s pioneering work led to the emergence of Neuroergonomics as a new scientific field. Neuroergonomics is defined as the study of the human brain in relation to performance at work and everyday settings (Parasuraman, 2003; Parasuraman and Rizzo, 2008). Since the advent of Neuroergonomics, significant progress has been made with respect to methodology and tools for the investigation of the brain and behavior at work. This is especially the case for neuroscientific methods where the availability of ambulatory hardware, wearable sensors, and advanced data analyses allow for imaging of brain dynamics in humans in applied environments. For neuroergonomics, the application of brain imaging in real-world scenarios is highly desirable as an investigation tool. Traditionally, brain imaging experiments in human factors research tend to avoid active behavior for fear of artifacts contaminating the signal of interest. Here, the development of new data analyses techniques as well as the combination of different methods providing complementary insights into brain and behavioral dynamics allow for new insights into Edited and reviewed by: the human-machine interaction. To overcome the problem of artifactual data in mobile recordings Mikhail Lebedev, and to allow analyses of brain activity in real working environments new portable sensors and Duke University, USA improved analyses approaches have to be developed. Hence, deployment of portable *Correspondence: technologies to real time settings could help assess cognitive and motivational states of personnel Klaus Gramann assigned to perform critical tasks. [email protected] THE “TRENDS IN NEUROERGONOMICS” RESEARCH TOPIC: A Received: 07 February 2017 BRIEF INTRODUCTION Accepted: 21 March 2017 Published: 05 April 2017 The eBook of this Frontiers Research Topic is divided into four sections, defined by the primary Citation: research methods used to address a variety of neuroergonomic research questions. The scientific Gramann K, Fairclough SH, topics range from air traffic control and automation, over mental load detection and the use of Zander TO and Ayaz H (2017) Editorial: Trends in Neuroergonomics. brain activity to control a system (brain computer interfaces, BCI), to physical work, rehabilitation, Front. Hum. Neurosci. 11:165. and training. Across the diverse research areas, the majority of studies in this Research Topic doi: 10.3389/fnhum.2017.00165 used (EEG), followed by functional near infrared spectroscopy (fNIRS),

Frontiers in Human | www.frontiersin.org 1 April 2017 | Volume 11 | Article 165 Gramann et al. Editorial: Trends in Neuroergonomics reflecting the constantly growing use of these methods in wider variety of control commands in motor imagery-based neuroergonomics. At the same time this eBook clearly BCIs might lead to an accelerate brain-computer communication demonstrates a trend to investigate physical and cognitive activity while Callan et al. increase response speed in flight simulation by outside standard laboratory settings, moving neuroergonomics using a passive BCI based on MEG. The former study provides “into the wild.” In addition, traditional methods like the insights into the use of control commands to increase BCI- measurement of eye movements, pupil metrics, (ECG), and based system communication while the latter study demonstrates established imaging approaches like functional magnetic the potential to decode motor intention faster than manual resonance imaging (fMRI) are used in combination with other control in response to hazardous change in the system interaction methods to better understand the physiological responses to cycle. Roy et al. investigate mental workload based on auditory cognitive or physical tasks and their coupling to hemodynamic evoked potentials. The authors present a new minimal intrusive changes. The different sections include original research articles, paradigm that paves the way to monitor operators’ mental state but also reviews and opinion pieces. Here, we provide short in real-life settings to allow adaption of the user interface without summaries as an orientation for the interested reader. interfering with the primary task. Caywood et al. increase the The first section in this eBook thus comprises studies that interpretability of BCI models by using the approach of Gaussian used EEG to investigate ergonomic research questions with three Process Regression for assessing cognitive workload. Ewing et al. studies using EEG in a mobile setting. The first of these by describe the development of an adaptive game system that Jungnickel and Gramann uses a mobile brain/body imaging measures spontaneous EEG activity in real-time in order to adjust approach (MoBI; Makeig et al., 2009; Gramann et al., 2012, the difficulty level of the game. In two studies the concept of a 2014) to investigate the brain and behavioral dynamics of human biocybernetic control loop (Fairclough, 2009) is introduced in participants interacting with dynamically moving objects. The detail with a particular emphasis on validating EEG measures results indicate increased activity in parietal regions when active experimentally prior to their incorporation into an adaptive game physical behavior as compared to standard laboratory button system. press behavior was required to respond to relevant changes in Studies using EEG in combination with other methods show the environment. The findings point to changes in brain dynamic that different physiological parameters can lead to an improved states dependent on the behavioral state. The study by Wascher understanding of the construct under investigation. Ko et al. et al. demonstrates that mobile EEG allows for a non-obtrusive demonstrate the advantage of integrating the high resolution in assessment of mental fatigue in natural working situations. The the time and spatial domain for EEG and fMRI, respectively, in a authors investigate EEG variations time-locked to eye-blinksasa stop-signal paradigm. Their results from multimodal recordings new tool to unobtrusively monitor cognitive processing in real- provide new insights into the complex brain networks underlying life environments. Mijovic´ et al. also use EEG in a naturalistic inhibitory control in naturalistic environments. Using EEG in work environment to show that instructed responses can increase combination with ECG and fNIRS, Ahn et al. investigate mental as reflected in brain dynamics without changes in fatigue in drivers. They show that a combination of different response parameters. The results point to the possibility to use physiological measures substantially improves the classification instructed responses to increase attentional processing without of sleep deprived or well-rested drivers. Scheer et al. investigate compromising work performance in manual assembly tasks. the demands on mental resources during a closed-loop steering Again, explicitly allowing movement of participants, Meinel task in simulated car driving scenarios. The results indicate an et al. demonstrate that EEG can be used to improve motor impact of steering demands on event-related EEG activity for rehabilitation approaches. Better performance in movement tasks task-irrelevant distractor probes allowing for an evaluation of can be achieved by identifying comodulation of different sources mental workload in steering environments. in the EEG before a movement is executed. The results provide The second section summarizes the use of fNIRS in traditional participant-specific prediction of performance fluctuations that stationary settings but also in new mobile applications. The could be used to enhance neuroergonomic and rehabilitation first study of these, Von Lühmann et al. describe the scenarios. The last study by Zander et al. investigates how well development of a wireless and low-cost open source fNIRS a passive brain-computer Interface can work in an autonomous hardware with details on system concept, hardware, software driving scenario using a dry EEG system. The results reveal and mechanical implementation. The proposed system was tested comfort issues but acceptable usability of the tested EEG system in a mental arithmetic BCI experiment. Mandrick et al. discuss and sufficient signal quality for use in an autonomous driving electrocortical and neurovascular measures with respect to the context. measurement of mental workload. They propose that EEG and A number of EEG-studies use the recorded brain electrical fNIRS are complementary methods in the context of applied signals for system interaction through brain-computer interfaces testing in the sense that the weakness of each approach, e.g., poor (BCIs, Zander and Kothe, 2011). In this context, Kirchner et al. spatial and temporal resolution, respectively, is counteracted by demonstrate that event-related potentials can be used on a single the strength of the other. They argue for a combined fNIRS-EEG trial level to infer task-engagement of an operator controlling approach to index neurovascular coupling during the assessment multiple robots and to adapt the man-machine interface to the of mental workload. individual operator. The results could be used to adapt the task In Bediz et al. the effects of supramaximal exercise on load to operators with different qualifications or capabilities cognitive task related oxygenation changes are investigated. to avoid mental overload. Alonso-Valerdi et al. suggest that a Performance in a task before and after

Frontiers in Human Neuroscience | www.frontiersin.org 2 April 2017 | Volume 11 | Article 165 Gramann et al. Editorial: Trends in Neuroergonomics exercise indicated higher task related activation changes in schizophrenia, anxiety disorders, and other emerging clinical prefrontal cortex post-exercise and higher cognitive task related areas. brain activation increase in high-performing participants. The The fourth and last section in this eBook then covers study by Carrieri et al. investigates the neural correlates of a research approaches using eye movement measures including cognitive/motor task in a virtual reality (VR) environment. The pupilometric methods and other peripheral physiological findings support the use of VR in combination with fNIRS as methods like ECG. The first study in this section by Causse et al. a very good platform for neuroergonomic studies to objectively uses EEG and pupilometry to investigate the impact of high evaluate cortical hemodynamic activity. Mckendrick et al. utilize working memory load on language processing during piloting. ultra-portable, wearable and miniaturized fNIRS sensors on The results demonstrate high working memory load to disrupt participants walking outdoors in the open air. The battery- visual and language processing and a subtle effect of congruency operated miniaturized system implementation was described that was observable only at an electrophysiological level. In the by Ayaz et al. (2013). The results of a spatial navigation task study by Leff et al. the authors use a collaborative gaze channel indicated greater mental capacity reserves for users with head (CGC) to detect and display trainer gaze behavior to trainees mounted displays but also unwanted attention capture and in surgery tasks. The results of a simulated robotic surgery task cognitive tunneling as indicated by hemodynamics measures. imply liberation of attentional resources with the use of CGC The final contribution in this section by Durantin et al. provides potentially improving the capability of trainees to attend to evidence for using Kalman filter as a suitable approach for real- additional safety critical events during the procedure. Causse time noise removal for fNIRS signals in ecological situations and et al. then demonstrate that the pupil diameter correlates with the development of BCI. The findings from working memory inattentional deafness in an air traffic control task with varying tasks indicate Kalman filter increased the performance of the perceptual and cognitive load. classification of task load levels based on brain signal. The final contribution to this Research Topic is a review Section three comprises studies using stimulation methods on neuroscientific methods in automation research by Drnec alone or in combination with other methods to investigate et al. The authors provide a comprehensive overview on stimulation-based improvement of motor or cognitive functions. neuroscientific methods in trust in automation research and The introductory commentary by Besson et al. prepares the summarize how neuroscience can improve interaction design. stage for this section by providing a critical commentary on existing transcranial direct current stimulation (tDCS) protocols CONCLUDING REMARKS to enhance and enhance performance in real- world settings. They argue that priming tDCS protocols have Neuroergonomics has demonstrated an incredible development significant potential to improve learning and motor performance. since the introduction of the field by Raja Parasuraman. This Callan et al. demonstrate the simultaneous use of tDCS and Research Topic demonstrates how different methods can be used fMRI to investigate the effect of neurostimulation on resting to better understand the mind, body, and brain at work and to state functional connectivity and behavioral performance. The create and design systems that are better adapted to and make results reveal greater spontaneous resting state activity for the use of the human information processing structures, including tDCS group with higher resting state functional connectivity the body and the brain. This research is important, because it for participants demonstrating performance improvement in a allows for a human-centered design of environments that include visual search task. Choe et al. investigate the use of tDCS along natural behaviors. with multimodal neuroimaging (EEG and fNIRS) demonstrating that tDCS stimulation to the dorsolateral prefrontal or left motor AUTHOR CONTRIBUTIONS cortex during flight simulation training enhances behavioral performance and changes neurophysiological measurements All authors listed, have made substantial, direct and intellectual (EEG and fNIRS) indicating improved skill acquisition consistent contribution to the work, and approved it for publication. with previous studies (Ayaz et al., 2012). The final contribution in this section is the review of Teo et al. providing a discussion FUNDING of the theoretical framework underlying the use of VR in combination with neuroimaging and as a This Research Topic gathers, among other contributions, therapeutic intervention for . The authors papers presented at the 11th Berlin Workshop Human-Machine provide evidence for the use of VR in treating motor and mental Systems, 2016 supported by a grant from the German Research disorders such as cerebral palsy, Parkinson’s disease, , Foundation (DFG GR2627/6-1) awarded to KG.

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Fairclough, S. H. (2009). Fundamentals of physiological computing. Interact. Zander, T. O., and Kothe, C. (2011). Towards passive brain–computer Comput. 21, 133–145. doi: 10.1016/j.intcom.2008.10.011 interfaces: applying brain–computer interface technology to human–machine Gramann, K., Ferris, D. P., Gwin, J., and Makeig, S. (2014). Imaging systems in general. J. Neural Eng. 8:025005. doi: 10.1088/1741-2560/8/2/ natural in action. Int. J. Psychophysiol. 91, 22–29. doi: 10.1016/ 025005 j.ijpsycho.2013.09.003 Gramann, K., Gwin, J. T., Ferris, D. P., Oie, K., Jung, T.-P., Lin, C.-T., et al. (2012). Conflict of Interest Statement: The authors declare that the research was Cognition in action: Imaging brain/body dynamics in mobile humans. Rev. conducted in the absence of any commercial or financial relationships that could Neurosci. 22, 593–608. doi: 10.1515/RNS.2011.047 be construed as a potential conflict of interest. Makeig, S., Gramann, K., Jung, T.-P., Sejnowski, T. J., and Poizner, H. (2009). Linking brain, mind and behavior. Int. J. Psychophysiol. 73, 95–100. Copyright © 2017 Gramann, Fairclough, Zander and Ayaz. This is an open-access doi: 10.1016/j.ijpsycho.2008.11.008 article distributed under the terms of the Creative Commons Attribution License (CC Parasuraman, R. (2003). Neuroergonomics: research and practice. Theor. Issues BY). The use, distribution or reproduction in other forums is permitted, provided the Ergon. Sci. 4, 5–20. doi: 10.1080/14639220210199753 original author(s) or licensor are credited and that the original publication in this Parasuraman, R., and Rizzo, M. (2008). Neuroergonomics: The Brain at Work. journal is cited, in accordance with accepted academic practice. No use, distribution Oxford: Oxford University Press. or reproduction is permitted which does not comply with these terms.

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